Print ISSN: 1811-9212

Online ISSN: 2617-3352

Keywords : Mobile robot


An Optimal Path Planning Algorithms for a Mobile Robot

Omar Abdul Razzaq Abdul Wahhab; .Ahmed S. Al-Araji1

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2021, Volume 21, Issue 2, Pages 44-58

The goal of navigating a mobile robot is to find the optimal path to direct its
movement, so path planning is the best solution to find the optimal path. Therefore, the
two most important problems of path planning must be solved; the first is that the path
must avoid collision with obstacles, and second it must reduce the length of the path to a
minimum. This paper will discuss finding the shortest path with the optimum cost function
by using the Chaotic Particle Swarm Optimization (CPSO), and A*, compare the results
between them and the proposed hybrid algorithm that combines A* and Chaotic Particle
Swarm Optimization (ACPSO) algorithms to enhance A* algorithm to find the optimal
path and velocities of the wheeled mobile robot. These algorithms are simulated by
MATLAB in a fixed obstacles environment to show the effectiveness of the proposed
algorithm in terms of minimum number of an evaluation function and the shortest path
length as well as to obtain the optimal or near optimal wheel velocities.

A Cognitive System Design for Mobile Robot Based on an Intelligent Algorithm

Ahmed S. Al-Araji1; Attarid K. Ahmed

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2018, Volume 18, Issue 2, Pages 1-16

This paper presents a cognitive system based on a nonlinear Multi-Input Multi-
Output (MIMO) Proportion Integral Derivative (PID) Modified Elman Neural Network
(MENN) controller and the Square Road Map (SRM) method to guide the mobile robot during
the continuous path-tracking with collision-free navigation through static obstacles. The
proposed cognitive system consists of two parts: the first part is to plan the desired path for the
mobile robot with the static obstacle environment in order to determine the target point and to
avoid the obstacles based on the proposed square road map algorithm. The second part is to
guide and track the wheeled mobile robot on the desired path equation based on the proposed
nonlinear MIMO-PID-MENN controller with the intelligent algorithm. The Particle Swarm
Optimization (PSO) is used to on-line tune the variable control parameters of the proposed
controller to get the optimal torques actions for the mobile robot platform. Based on using the
MATLAB package (2017), the numerical simulation results show that the proposed cognitive
system has high accuracy for planning the desired path equation in terms of avoiding the static
obstacles with smooth and short distance and generating a perfect torque action of (0.7 N.m)
without a saturation state of (3.07 N.m), which leads to minimize the tracking pose error for
the mobile robot to the zero value approximation. These results were confirmed by a
comparative study with different nonlinear PID controller types in terms of number of
iterations and the performance index.

Enhanced Genetic Algorithm Based on Node Codes for Mobile Robot Path Planning

Dr. Mohamed Jasim Mohamed; Mrs. Farah S. Khoshaba

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2012, Volume 12, Issue 2, Pages 69-80

Abstract: In this paper, a new Enhanced Genetic Algorithm (EGA) is used to find the best global path planning for a mobile robot according to a specific criterion. The EGA is enhanced by a new encoding method, new initial population creation method, new crossover and mutation operations as well as new additional operations correction operation and classification operation. The study considers the case when the mobile robot works in a known static environment. The new proposed algorithm is built to help the mobile robot to choose the shortest path without it colliding with the obstacles allocated in a working known environment. The use of grid map in the environment helps to locate nodes on the map where all nodes are assigned by coordinate values. The start and the target nodes of the required path are given prior to the proposed algorithm. Each node represents a landmark that the mobile robot either passes through only one time or never passes through during its journey from start node to the target node. Two examples of known static mobile robot environments with many obstacles in each one are studied and the proposed algorithm is applied on them. The results show that the proposed algorithm is very reliable, accurate, efficient and fast to give the best global path planning for the two cases.

Genetic Algorithm Using Sub-path Codes for Mobile Robot Path Planning

Dr. Mohamed Jasim Mohamed

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2012, Volume 12, Issue 1, Pages 104-117

In this paper, a new method for finding global optimal path planning is
proposed using a Genetic Algorithm (GA). A map of known static environment as well
as a start node and a target node connecting an optimal path which is required to be
found are given beforehand. The chosen nodes in a known static environment are
connected by sub-paths among each other. Each path is represented by a series of subpaths
which connect the sequential nodes to form this path. Each sub-path radiating
from each node is labeled by an integer. The chromosome code of a path is a string of
series integers that represent the labels of sub-paths which are passed through traveling
from start node to target node. Two factors are integrated into a fitness function of the
proposed genetic algorithm: the feasibility of collision avoidance path and the shortest
distance of path. Two examples of known static environment maps are taken in this
study with different numbers of obstacles and nodes. Simulation results show the
effectiveness and feasibility of the proposed GA using sub-path codes to find optimum
path planning for mobile robot.

DESIGN AND SIMULATION OF FUZZY LIKE PD CONTROLLER FOR AUTONOMOUS MOBILE ROBOT1

Dr. Muna H. Saleh; Dr. Mazin Z. Othman; Dr. Arif A. Al-Qassar

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2011, Volume 11, Issue 2, Pages 36-43

Abstract:
Mobile robot is a mechanical device capable of moving in an environment with a certain degree of autonomy. The main goal of this work is to design, and simulate an intelligent controller for autonomous mobile robot named Fuzzy like PD Controller, as the test bed for future development of an intelligent vehicle. The fuzzy algorithm was implemented using a combination of three different units of fuzzy logic systems that controls two identical DC servo motors to implement the requirements of the safety navigation of the mobile robot. The paper implies computer simulations in MATLAB platform using a step input to demonstrate the ability of each controller to accommodate the sudden changes along the motion of the mobile robot.